Foodservice enters the age of AI

Foodservice enters the age of AI

Consumers rely on AI every day, even if its influence is not always obvious, but the foodservice sector is yet to embrace it fully. Jim Banks looks at how kitchen design, customer interaction, and efficiency are set to be revolutionized.

Artificial intelligence (AI) is everywhere, whether we realize it or not. It powers the algorithms that compile our Spotify playlists and suggest YouTube videos for us, and it shapes our social media interactions. It generates more and more content that we consume – words, music, and images – and it supports decision-making in every industry from manufacturing to medicine. AI’s ability to access, analyze and interpret vast amounts of data at a speed far beyond that of the human brain is undoubtedly a great asset, although it raises many questions about how much responsibility should be handed over to automated systems, and how those systems work with and for humans. These questions apply to the foodservice industry as much as any other, even if the sector has been slower to adopt AI.

So, what can AI do in kitchen operations to make foodservice operations quicker and more efficient? How can it enhance the customer experience? And does the commercial foodservice industry understand how AI can help? Joseph Alfieri, regional vice president of Bon Appetit Management Company, an onsite restaurant company offering full foodservice management to corporations, universities, museums, and specialty venues, has a clear answer for that last question. “No, the industry absolutely does not have a good understanding of what AI can and cannot do,” he says. “

Large corporations are starting to adapt to it. Burger King®, McDonald’s® and other large chains are using it in their customer service portals, and some are working on AIsupported face-recognition technology, so that when customers walk in it knows their order from past transactions. “Smaller operations are not on top of it yet, because of this continuous pivoting,” adds Alfieri. “They are always adapting to their clients’ needs, but they are not looking at AI in their operations as a whole, yet. AI could help with HR problems perhaps, or inventory management and ordering processes. Chefs can ask AI to create a menu by giving it different filters – vegan, allergenic and so on – but chefs are sentimental and don’t want to use other people’s menus. Their egos stop them letting AI do that job.”

FAST CASUAL FAST TRACKS AI

To see how AI is impacting commercial foodservice operations, it pays to look at the QSR sector, which is leading the way in terms of adoption. A forthcoming white paper, The Current and Future of Artificial Intelligence and Robotics in the Fast Casual Restaurant Industry: Service and Production, lays out many key trends that will affect the wider industry. In it, author John Egnor FCSI, design evolutionist at JME Design, notes that the fast casual sector is starting to transform. The combination of AI and robotics is reshaping both service and production, enhancing efficiency, reducing costs, and improving customer experience.

So far, this is most apparent in tasks such as order-taking, food preparation, and delivery – with Sweetgreen® and Chipotle® among the leading adopters – but many others also see the potential to further streamline operations, personalize customer interactions, and address labor challenges. So how do these restaurant chains envisage AI achieving these goals, and where will it be applied? Part of the answer to that question has already emerged, in the shape of AI-powered ordering systems. White Castle®, for example – generally seen as the world’s first fast-food hamburger chain – has piloted voice AI for drive-thru orders to reduce waiting times and free up staff for other tasks.

Similarly, AI is already being used to analyze point-of-sale (POS) data and customer preferences to deliver more personalized order recommendations. OpenTable®’s integration with POS systems, for example, provides real-time insights into guest behavior, enabling staff to anticipate needs and upsell more effectively.

ON THE FLIP SIDE

AI and robotics are increasingly finding applications behind the counter as well, reshaping kitchen workflows to be more efficient and consistent. Robotic food preparation is already happening. The Flippy robot from Miso Robotics, for example – used in 15 White Castle restaurants and several other chains – automatically flips burgers and cleans the grill.

AI is finding its way into quality control and safety as well, using data from sensors and camera systems to ensure consistent cooking temperatures and detect anomalies. AI-powered predictive analytics can also optimize inventory by forecasting demand based on historical data of what sells and when, leading to less waste and more efficient ordering processes. Although foodservice operations outside the QSR sector may not be interested in robotic preparation systems – such as Sweetgreen’s Infinite Kitchen, which automates salad assembly to save time – the personalization and inventory management capabilities of AI could be a better fit.

Egnor firmly believes that AI will find its place in foodservice in the not-too-distant future: “It will be a tool to control the production of menu items, with cues, with direction, and knowing the history of a product. If a McDonald’s usually serves 300 hamburgers at lunch time, then AI can queue the preparation process early enough for them to be ready in time.” It will also be able to make decisions based on more nuanced information.

“You can add in other data, such as weather information or local news reports, which will affect the number of orders,” he adds. “That level of integration of situational knowledge to control inventory and production schedules can save on waste. So, the next step is looking at analytics for what to produce and when.”

A FUTURE OF AI-ENABLED AUTOMATION

For Egnor, robotics is not yet where AI needs it to be. Consequently, the first gamechanging application of AI is likely to come through its role as a forecasting tool, with more applications soon to follow. Front-of-house applications such as voice ordering will continue to evolve as advanced voice AI capability improves, and by leveraging big data – social media, loyalty programs, dietary preferences and more – AI might usher in the age of hyper-personalization. In the kitchen, higher levels of automation will arrive, reducing human intervention to a minimum.

Smart kitchens with digital twins could, according to Egnor, use AI to simulate and optimize workflows to create better kitchen plans, predict equipment failure, adjust cooking parameters in real time, and potentially reduce energy consumption by around 20%. Stefano Raimondi, R&D Director at Rancilio Group, believes AI will also have an impact on beverages, and Rancilio is among the manufacturers engaging in the development of equipment with integrated AI functionality.

“AI can simplify the search of technical documents if there is an error with a machine, or optimize the parameters of the recipe, or recognize a barista in front of the machine to change settings to their unique requirements,” he says. “The state of the art is a system that can summarize information from hundreds of documents. The problem used to be finding the data, but with IoT we now have too much data, so we need to address the problem of analyzing it,” adds Raimondi.

SHARED EXPERIENCE

“AI will be used to simplify life for the technical team, providing more support for technicians who don’t necessarily understand coffee,” adds Raimondi. “We could use a generic technician for dishwashers and coffee machines, for example, because we could move the relevant knowledge from a person to an AI system.” Meanwhile, forecasting order patterns using big data is as relevant to beverages as it is to food preparation.

Raimondi foresees a time when AI is used to propose alternative recipes according to the time of day. “AI could help operators create something closer to individuals’ needs – more personalized and customized – through integration of data and by face recognition,” he says. He also believes AI will be used to simplify settings, improve consistency in automatic machines with grinders inside, and optimize recipe configuration. In the early days, adoption of AI could raise concerns about cost, scalability, and the need for a human element in dining.

Over time, however, it will become part of the fabric of foodservice. “When chefs see what it can do, they say: ‘Wow, where was this all my life?’” says Alfieri. “My team probably feeds 15- 20,000 people per day in various locations, and I use AI for two or three hours per day to evaluate standard operating procedures, safety protocols, and food trends, and to create financial forecasts and budgets. It is a useful tool if you know what to ask it.”

There remain many unknowns when it comes to AI and its limitations – and how to best apply its capabilities. However, while it is not yet baked into kitchen appliances, it is certainly defining the next wave of kitchen planning, workflow design, and forecasting. The one thing you cannot do with AI is ignore it.

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